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ATLAS
Abstract:
This thesis describes the development and performance of a new approach for reconstructing and identifying highly boosted Z → e+e- decays with the ATLAS detector. A Z → e+e- candidate decay is reconstructed via a single jet, clustered via the anti-kt algorithm using a radius parameter of 0.4. For the identification of the Z → e+e- decay, a deep neural network, trained on the jet properties including inner detector and calorimeter information, is used. Finally, the Z → e+e- identification and reconstruction approach is tested in the search for a Z’ boson based on Monte Carlo simulations of the data taken with the ATLAS detector during the LHC Run 2. Expected exclusion limits on the production cross section times branching ratio at 95% confidence level are determined.
